Facial Recognition System

Gaining Importance of Facial Recognition System

A facial recognition system uses Biometric Technology that uniquely identifies a person by analyzing his facial textures and shape. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database.

Facial recognition is gaining a huge visibility due to its contactless and non-invasive process compared to other biometric technologies like voice recognition, skin texture recognition, iris recognition, and fingerprint scanning, etc. According to Allied market research, Facial Recognition is expected to grow to $9.6 billion by 2022, registering a CAGR of 21.3% during the forecast period 2016-2022.

While there are many features related to facial identification technology , it is important to understand the important features that assure system performance, reliability with live face detection, simultaneous multiple face recognition and fast face matching in 1-to-1 and 1-to-many modes.

Important Features of a Face Recognition System for Attendance and Access Control

  • Quality of the Camera that records the image : Face recognition accuracy heavily depends on the quality of a face image. Image quality during enrollment is important, as it influences the quality of the face template. 2 MP is the minimal recommended camera for a face detection.
  • Face Recognition distance : 32 pixels is the recommended minimal distance between eyes for a face on image or video stream to perform face template extraction reliably. 64 pixels or more recommended for better face recognition results. Note that this distance should be native, not achieved by resizing an image.
  • No of images captured during enrollment : Several images during enrollment are recommended for better facial template quality which results in improvement of recognition quality and reliability.
  • Persons wearing face masks or sunglasses should be recognized without separate enrollment: This is a specific feature during which the software should disable the face quality and ensure that no extra images are required to identify a person.
  • Range of Angles for the face image: The face recognition engine has certain tolerance to face posture. The horizontal and the vertical range of face angle tilt should be tolerant keeping the users in mind. Minimal ±15 degrees default value is the fastest setting which is usually sufficient for most near-frontal face images.
  • Face Recognition Duration : It is defined as time taken to identify a person. As the name suggests, the smaller the number, the better it is. However, the number of users can help decide on this feature, more so since the lesser duration machines will be more complex and hence expensive.
  • Different kind of interfaces : Biometric interfaces comprise the methods by which one biometric system component communicates with another. These components may be devices, software, or entire systems. Example : RS-485, Wiegand interface, USB, TCP/IP and  Alarms
  • Multiple authentication modes : Biometric authentication is a form of security that measures and matches biometric features of a user to verify that a person trying to access a particular device is authorized to do so. Multi authentication mode can be achieved by combining multiple biometric patterns in conjunction with a traditional password or secondary device that supplements the biometric verification. Multiple authentication modes feature which combines more than one authentication mode should be supported to ensure 100% reliability of the system. Example: Face, fingerprint, iris,palm,password, proximity card. Combination of one or two methods along with facial recognition makes it more secure.
Facial Recognition Hikvision

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